The real-world tracking applications meet a number of difficulties caused by the presence of different kinds of uncertainty - unknown or not precisely known system model and random processes’ statistics or due to abrupt changes in the system modes of functioning. These problems are especially complicated in the marine navigation practice, where the commonly used simple models of rectilinear or curvilinear target motions do not match to the highly non-linear dynamics of the manoeuvring ship motion. A solution of these problems is to derive more adequate descriptions of the real ship dynamics and to design adaptive estimation algorithms. After analysis of basic hydrodynamic models, new ship models are derived in the paper. They are implemented in two versions of the recently very popular Interacting Multiple Model (IMM) algorithm. The first one is a standard IMM version using preliminary defined fixed structure (FS) of models. They represent various modes of ship motion, distinguished by their rate of turns. The same rate of turn is additionally adjusted in the proposed new augmented versions of the IMM (AIMM) algorithm by using FS and variable structure (VS) of adaptive models estimating the current change of the system control parameters. The obtained Monte Carlo simulation results show that the VS AIMM algorithm outperforms the FS AIMM and FS IMM algorithms with respect to accuracy and adaptability.